{smcl}
{* 23oct2020}{...}
{cmd:help moremata}{...}
{right:{browse "http://github.com/benjann/moremata/"}}
{hline}

{title:Title}

{p 4 4 2}
{bf:moremata -- Various Mata functions}


{title:Contents}

{col 5}  {bf:Online}
{col 5}{bf:help entry{col 22}Function{col 41}Purpose}
{col 5}{hline}

{col 5}   {c TLC}{hline 18}{c TRC}
{col 5}{hline 3}{c RT}{it: Scalar functions }{c LT}{hline}
{col 5}   {c BLC}{hline 18}{c BRC}

{col 5}{bf:{help mf_mm_kern:mm_kern()}}{...}
{col 22}{cmd:mm_kern()}{...}
{col 41}various kernel functions
{col 22}{cmd:mm_kint()}{...}
{col 41}kernel integral functions
{col 22}{cmd:mm_kderiv()}{...}
{col 41}kernel derivative functions
{col 22}{cmd:mm_kdel0()}{...}
{col 41}canonical bandwidth of kernel

{col 5}   {c TLC}{hline 23}{c TRC}
{col 5}{hline 3}{c RT}{it: Statistical functions }{c LT}{hline}
{col 5}   {c BLC}{hline 23}{c BRC}

{col 5}{it:Quantiles, ranks, frequencies, & summary statistics}

{col 5}{bf:{help mf_mm_quantile:mm_quantile()}}{...}
{col 22}{cmd:mm_quantile()}{...}
{col 41}compute quantiles
{col 22}{cmd:mm_median()}{...}
{col 41}compute median
{col 22}{cmd:mm_iqrange()}{...}
{col 41}compute inter-quartile range

{col 5}{bf:{help mf_mm_ecdf:mm_ecdf()}}{...}
{col 22}{cmd:mm_ecdf()}{...}
{col 41}compute cumulative distribution function
{col 22}{cmd:mm_ecdf2()}{...}
{col 41}cumulative distribution at unique values

{col 5}{bf:{help mf_mm_ranks:mm_ranks()}}{...}
{col 22}{cmd:mm_ranks()}{...}
{col 41}compute ranks/cumulative frequencies

{col 5}{bf:{help mf_mm_relrank:mm_relrank()}}{...}
{col 22}{cmd:mm_relrank()}{...}
{col 41}compute relative ranks (grade transformation)

{col 5}{bf:{help mf_mm_density:mm_density()}}{...}
{col 22}{cmd:mm_density()}{...}
{col 41}compute density (Stata 11 required)

{col 5}{bf:{help mf_mm_ddens:mm_ddens()}}{...}
{col 22}{cmd:mm_ddens()}{...}
{col 41}compute density by diffusion

{col 5}{bf:{help mf_mm_freq:mm_freq()}}{...}
{col 22}{cmd:mm_freq()}{...}
{col 41}compute frequency counts

{col 5}{bf:{help mf_mm_histogram:mm_histogram()}}{...}
{col 22}{cmd:mm_histogram()}{...}
{col 41}produce histogram data

{col 5}{bf:{help mf_mm_mgof:mm_mgof()}}{...}
{col 22}{cmd:mm_mgof()}{...}
{col 41}multinomial goodness-of-fit tests

{col 5}{bf:{help mf_mm_collapse:mm_collapse()}}{...}
{col 22}{cmd:mm_collapse()}{...}
{col 41}summary statistics by subgroups
{col 22}{cmd:_mm_collapse()}{...}
{col 41}summary statistics by subgroups

{col 5}{bf:{help mf_mm_gini:mm_gini()}}{...}
{col 22}{cmd:mm_gini()}{...}
{col 41}Gini coefficient

{col 5}{bf:{help mf_mm_nobs:mm_nobs()}}{...}
{col 22}{cmd:mm_nobs()}{...}
{col 41}number of observations

{col 5}{it:Sampling, resampling, & combinations}

{col 5}{bf:{help mf_mm_sample:mm_sample()}}{...}
{col 22}{cmd:mm_sample()}{...}
{col 41}draw random sample
{col 22}{cmd:mm_srswr()}{...}
{col 41}SRS with replacement
{col 22}{cmd:mm_srswor()}{...}
{col 41}SRS without replacement
{col 22}{cmd:mm_upswr()}{...}
{col 41}UPS with replacement
{col 22}{cmd:mm_upswor()}{...}
{col 41}UPS without replacement

{col 5}{bf:{help mf_mm_bs:mm_bs()}}{...}
{col 22}{cmd:mm_bs()}{...}
{col 41}bootstrap estimation
{col 22}{cmd:mm_bs2()}{...}
{col 41}bootstrap estimation
{col 22}{cmd:mm_bs_report()}{...}
{col 41}report bootstrap results

{col 5}{bf:{help mf_mm_jk:mm_jk()}}{...}
{col 22}{cmd:mm_jk()}{...}
{col 41}jackknife estimation
{col 22}{cmd:mm_jk_report()}{...}
{col 41}report jackknife results

{col 5}{bf:{help mf_mm_subset:mm_subset()}}{...}
{col 22}{cmd:mm_subset()}{...}
{col 41}obtain subsets, one at a time
{col 22}{cmd:mm_composition()}{...}
{col 41}obtain compositions, one by one
{col 22}{cmd:mm_ncompositions()}{...}
{col 41}determine number of compositions
{col 22}{cmd:mm_partition()}{...}
{col 41}obtain partitions, one at a time
{col 22}{cmd:mm_npartitionss()}{...}
{col 41}determine number of partitions
{col 22}{cmd:mm_rsubset()}{...}
{col 41}draw random subset
{col 22}{cmd:mm_rcomposition()}{...}
{col 41}draw random composition

{col 5}{it:Matching/reweighting}

{col 5}{bf:{help mf_mm_greedy:mm_greedy()}}{...}
{col 22}{cmd:mm_greedy()}{...}
{col 41}one-to-one and one-to-many matching w/o replacement
{col 22}{cmd:mm_greedy2()}{...}
{col 41}like {cmd:mm_greedy()}, but returning edge-list
{col 22}{cmd:mm_greedy_pairs()}{...}
{col 41}transform result from {cmd:mm_greedy()} into edge-list

{col 5}{bf:{help mf_mm_ebal:mm_ebal()}}{...}
{col 22}{cmd:mm_ebal()}{...}
{col 41}entropy balancing (Stata 11 required)

{col 5}{it:Means, variances, & correlations}

{col 5}{bf:{help mf_mm_colvar:mm_colvar()}}{...}
{col 22}{cmd:mm_colvar()}{...}
{col 41}variance, by column
{col 22}{cmd:mm_meancolvar()}{...}
{col 41}mean and variance, by column
{col 22}{cmd:mm_variance0()}{...}
{col 41}population variance
{col 22}{cmd:mm_meanvariance0()}{...}
{col 41}mean and population variance
{col 22}{cmd:mm_mse()}{...}
{col 41}mean squared error
{col 22}{cmd:mm_colmse()}{...}
{col 41}mean squared error, by column
{col 22}{cmd:mm_sse()}{...}
{col 41}sum of squared errors
{col 22}{cmd:mm_colsse()}{...}
{col 41}sum of squared errors, by column

{col 5}{bf:{help mf_mm_mloc:mm_mloc()}}{...}
{col 22}{cmd:mm_mloc()}{...}
{col 41}robust M estimate of location
{col 22}{cmd:mm_mscale()}{...}
{col 41}robust M estimate of scale

{col 5}{bf:{help mf_mm_hl:mm_hl()}}{...}
{col 22}{cmd:mm_hl()}{...}
{col 41}Hodges-Lehmann location estimator
{col 22}{cmd:mm_qn()}{...}
{col 41}Qn scale coefficient
{col 22}{cmd:mm_mc()}{...}
{col 41}Medcouple skewness measure

{col 5}{it:Distributions}

{col 5}{bf:{help mf_mm_benford:mm_benford()}}{...}
{col 22}{cmd:mm_benford()}{...}
{col 41}Benford distribution

{col 5}{bf:{help mf_mm_cauchy:mm_cauchy()}}{...}
{col 22}{cmd:mm_cauchy()}{...}
{col 41}cumulative Cauchy-Lorentz dist.
{col 22}{cmd:mm_cauchyden()}{...}
{col 41}Cauchy-Lorentz density
{col 22}{cmd:mm_cauchytail()}{...}
{col 41}reverse cumulative Cauchy-Lorentz
{col 22}{cmd:mm_invcauchy()}{...}
{col 41}inverse cumulative Cauchy-Lorentz

{col 5}{bf:{help mf_mm_rbinomial:mm_rbinomial()}}{...}
{col 22}{cmd:mm_rbinomial()}{...}
{col 41}generate binomial random numbers
{col 22}{cmd:mm_cebinomial()}{...}
{col 41}cond. expect. of binomial r.v.

{col 5}   {c TLC}{hline 30}{c TRC}
{col 5}{hline 3}{c RT}{it: Other mathematical functions }{c LT}{hline}
{col 5}   {c BLC}{hline 30}{c BRC}

{col 5}{bf:{help mf_mm_root:mm_root()}}{...}
{col 22}{cmd:mm_root()}{...}
{col 41}Brent's univariate zero finder

{col 5}{bf:{help mf_mm_nrroot:mm_nrroot()}}{...}
{col 22}{cmd:mm_nrroot()}{...}
{col 41}Newton-Raphson zero finder

{col 5}{bf:{help mf_mm_minim:mm_minim()}}{...}
{col 22}{cmd:mm_minim()}{...}
{col 41}Brent's univariate minimum finder

{col 5}{bf:{help mf_mm_finvert:mm_finvert()}}{...}
{col 22}{cmd:mm_finvert()}{...}
{col 41}univariate function inverter

{col 5}{bf:{help mf_mm_integrate:mm_integrate()}}{...}
{col 22}{cmd:mm_integrate_sr()}{...}
{col 41}univariate function integration (Simpson's rule)
{col 22}{cmd:mm_integrate_38()}{...}
{col 41}univariate function integration (Simpson's 3/8 rule)

{col 5}{bf:{help mf_mm_ipolate:mm_ipolate()}}{...}
{col 22}{cmd:mm_ipolate()}{...}
{col 41}linear interpolation
{col 22}{cmd:_mm_ipolate()}{...}
{col 41}linear interpolation (assuming sorted data)
{col 22}{cmd:mm_fastipolate()}{...}
{col 41}linear interpolation (assuming sorted and unique data)

{col 5}{bf:{help mf_mm_polint:mm_polint()}}{...}
{col 22}{cmd:mm_polint()}{...}
{col 41}polynomial inter-/extrapolation

{col 5}{bf:{help mf_mm_sqrt:mm_sqrt()}}{...}
{col 22}{cmd:mm_sqrt()}{...}
{col 41}square root of a symmetric positive definite matrix

{col 5}   {c TLC}{hline 21}{c TRC}
{col 5}{hline 3}{c RT}{it: Graphical functions }{c LT}{hline}
{col 5}   {c BLC}{hline 21}{c BRC}

{col 5}{bf:{help mf_mm_plot:mm_plot()}}{...}
{col 22}{cmd:mm_plot()}{...}
{col 41}Draw twoway plot
{col 22}{cmd:_mm_plot()}{...}
{col 41}Draw twoway plot

{col 5}   {c TLC}{hline 26}{c TRC}
{col 5}{hline 3}{c RT}{it: Matrix utility functions }{c LT}{hline}
{col 5}   {c BLC}{hline 26}{c BRC}

{col 5}{bf:{help mf_mm_group:mm_group()}}{...}
{col 22}{cmd:mm_group()}{...}
{col 41}create group index
{col 22}{cmd:_mm_group()}{...}
{col 41}create group index, without sorting

{col 5}{bf:{help mf_mm_panels:mm_panels()}}{...}
{col 22}{cmd:mm_panels()}{...}
{col 41}identify nested panel structure
{col 22}{cmd:_mm_panels()}{...}
{col 41}identify panel sizes
{col 22}{cmd:mm_npanels()}{...}
{col 41}identify number of panels

{col 5}{bf:{help mf_mm_nunique:mm_nunique()}}{...}
{col 22}{cmd:mm_nunique()}{...}
{col 41}count number of unique values in vector
{col 22}{cmd:mm_unique()}{...}
{col 41}obtain unique values from vector
{col 22}{cmd:mm_unique_tag()}{...}
{col 41}tag unique values in vector
{col 22}{cmd:mm_nuniqrows()}{...}
{col 41}count number of unique rows in matrix
{col 22}{cmd:mm_uniqrows()}{...}
{col 41}obtain unique rows from matrix
{col 22}{cmd:mm_uniqrows_tag()}{...}
{col 41}tag unique rows in matrix

{col 5}{bf:{help mf_mm_diff:mm_diff()}}{...}
{col 22}{cmd:mm_diff()}{...}
{col 41}compute lagged differences
{col 22}{cmd:mm_rowdiff()}{...}
{col 41}compute lagged differences within rows
{col 22}{cmd:mm_coldiff()}{...}
{col 41}compute lagged differences within columns

{col 5}{bf:{help mf_mm_isconstant:mm_isconstant()}}{...}
{col 22}{cmd:mm_isconstant()}{...}
{col 41}whether matrix is constant
{col 22}{cmd:mm_issorted()}{...}
{col 41}whether vector is sorted

{col 5}{bf:{help mf_mm_colrunsum:mm_colrunsum()}}{...}
{col 22}{cmd:mm_colrunsum()}{...}
{col 41}running sum of each column

{col 5}{bf:{help mf_mm_prod:mm_prod()}}{...}
{col 22}{cmd:mm_prod()}{...}
{col 41}compute product of elements in matrix
{col 22}{cmd:mm_rowprod()}{...}
{col 41}compute product within rows
{col 22}{cmd:mm_colprod()}{...}
{col 41}compute product within columns

{col 5}{bf:{help mf_mm_linbin:mm_linbin()}}{...}
{col 22}{cmd:mm_linbin()}{...}
{col 41}linear binning
{col 22}{cmd:mm_fastlinbin()}{...}
{col 41}fast linear binning
{col 22}{cmd:mm_exactbin()}{...}
{col 41}exact binning
{col 22}{cmd:mm_fastexactbin()}{...}
{col 41}fast exact binning
{col 22}{cmd:mm_makegrid()}{...}
{col 41}equally spaced grid points

{col 5}{bf:{help mf_mm_seq:mm_seq()}}{...}
{col 22}{cmd:mm_seq()}{...}
{col 41}generate regular sequence

{col 5}{bf:{help mf_mm_cut:mm_cut()}}{...}
{col 22}{cmd:mm_cut()}{...}
{col 41}categorize data vector

{col 5}{bf:{help mf_mm_posof:mm_posof()}}{...}
{col 22}{cmd:mm_posof()}{...}
{col 41}find element in vector

{col 5}{bf:{help mf_mm_which:mm_which()}}{...}
{col 22}{cmd:mm_which()}{...}
{col 41}positions of nonzero elements

{col 5}{bf:{help mf_mm_locate:mm_locate()}}{...}
{col 22}{cmd:mm_locate()}{...}
{col 41}search an ordered vector
{col 22}{cmd:mm_hunt()}{...}
{col 41}consecutive search

{col 5}   {c TLC}{hline 31}{c TRC}
{col 5}{hline 3}{c RT}{it: Matrix manipulation functions }{c LT}{hline}
{col 5}   {c BLC}{hline 31}{c BRC}

{col 5}{bf:{help mf_mm_clip:mm_clip()}}{...}
{col 22}{cmd:mm_clip()}{...}
{col 41}clip/limit the values in a matrix
{col 22}{cmd:mm_clipmin()}{...}
{col 41}limit the minimum
{col 22}{cmd:mm_clipmax()}{...}
{col 41}limit the maximum

{col 5}{bf:{help mf_mm_cond:mm_cond()}}{...}
{col 22}{cmd:mm_cond()}{...}
{col 41}matrix conditional operator

{col 5}{bf:{help mf_mm_expand:mm_expand()}}{...}
{col 22}{cmd:mm_expand()}{...}
{col 41}duplicate single rows/columns
{col 22}{cmd:_mm_expand()}{...}
{col 41}duplicate rows/columns in place
{col 22}{cmd:mm_repeat()}{...}
{col 41}duplicate contents as a whole
{col 22}{cmd:_mm_repeat()}{...}
{col 41}duplicate contents in place

{col 5}{bf:{help mf_mm_sort:mm_sort()}}{...}
{col 22}{cmd:mm_sort()}{...}
{col 41}stable sorting
{col 22}{cmd:mm_order()}{...}
{col 41}stable ordering

{col 5}{bf:{help mf_mm_unorder2:mm_unorder2()}}{...}
{col 22}{cmd:mm_unorder2()}{...}
{col 41}stable version of {cmd:unorder()}
{col 22}{cmd:mm_jumble2()}{...}
{col 41}stable version of {cmd:jumble()}
{col 22}{cmd:mm__jumble2()}{...}
{col 41}stable version of {cmd:_jumble()}

{col 5}   {c TLC}{hline 18}{c TRC}
{col 5}{hline 3}{c RT}{it: String functions }{c LT}{hline}
{col 5}   {c BLC}{hline 18}{c BRC}

{col 5}{bf:{help mf_mm_pieces:mm_pieces()}}{...}
{col 22}{cmd:mm_pieces()}{...}
{col 41}break string into pieces
{col 22}{cmd:mm_npieces()}{...}
{col 41}count number of pieces
{col 22}{cmd:_mm_npieces()}{...}
{col 41}count number of pieces

{col 5}{bf:{help mf_mm_regexr:mm_regexr()}}{...}
{col 22}{cmd:mm_regexr()}{...}
{col 41}regular expression replace

{col 5}{bf:{help mf_mm_invtokens:mm_invtokens()}}{...}
{col 22}{cmd:mm_invtokens()}{...}
{col 41}reverse of {cmd:tokens()}

{col 5}{bf:{help mf_mm_realofstr:mm_realofstr()}}{...}
{col 22}{cmd:mm_realofstr()}{...}
{col 41}convert string into real

{col 5}{bf:{help mf_mm_strexpand:mm_strexpand()}}{...}
{col 22}{cmd:mm_strexpand()}{...}
{col 41}expand string argument

{col 5}   {c TLC}{hline 15}{c TRC}
{col 5}{hline 3}{c RT}{it: I/O functions }{c LT}{hline}
{col 5}   {c BLC}{hline 15}{c BRC}

{col 5}{bf:{help mf_mm_matlist:mm_matlist()}}{...}
{col 22}{cmd:mm_matlist()}{...}
{col 41}display a (real) matrix

{col 5}{bf:{help mf_mm_insheet:mm_insheet()}}{...}
{col 22}{cmd:mm_insheet()}{...}
{col 41}read spreadsheet file
{col 22}{cmd:mm_infile()}{...}
{col 41}read free-format file
{col 22}{cmd:mm_outsheet()}{...}
{col 41}write spreadsheet file

{col 5}   {c TLC}{hline 23}{c TRC}
{col 5}{hline 3}{c RT}{it: Programming functions }{c LT}{hline}
{col 5}   {c BLC}{hline 23}{c BRC}

{col 5}{bf:{help mf_mm_callf:mm_callf()}}{...}
{col 22}{cmd:mm_callf()}{...}
{col 41}pass optional args to function
{col 22}{cmd:mm_callf_setup()}{...}
{col 41}setup for {cmd:mm_callf()}
{col 5}{hline}


{title:Description}

{p 4 4 2}
The functions above are general-purpose add-ons to official Mata.


{title:Author}

{p 4 4 2} Ben Jann, University of Bern, ben.jann@soz.unibe.ch

{p 4 4 2} The Cauchy-Lorentz distribution functions were provided by
Christopher F Baum, Boston College.

{p 4 4 2}
    Thanks for citing this software as follows:

{p 8 8 2}
    Jann, B. 2005. moremata: Stata module (Mata) to provide various functions. Available from
    http://ideas.repec.org/c/boc/bocode/s455001.html.


{title:Also see}

{p 4 13 2}
Online:  help for {bf:{help mata}}
